Application of Wearable Motion Sensor in Business English Teaching

Dan Lu1 and Fen Guo2

  1. School of Foreign Languages, Shunde Polytechnic, Shunde 528300, Guangdong, China
  2. School of Software Engineering, South China University of Technology, Guangzhou, 510006, China


With the advancement of science and technology, portable motion sensors are becoming increasingly popular in life and have become a research point for improving life and learning, and are widely used in medical care and smart terminals. Based on the advantages of portable motion sensors, this paper focuses on its application in learning English business. Collects speech information through special motion sensors, analyzes the accuracy of students' reading through speech recognition, to help students better learn business English. Firstly, the wearable sensor is used to collect and preprocess the speech information of students' business English reading as the input of speech recognition. Secondly, the linear predictive cepstrum coefficient (LPCC) and Meier frequency cepstrum coefficient (MFCC) of students' business English reading speech are extracted, and the mixed parameters of LPCC and MFCC are taken as speech features. Finally, the correctness of reading speech is recognized by combining HMM and WNN. Through the simulation analysis of students' reading speech recognition, it is shown that the speech recognition based on wearable motion sensor is feasible and the recognition method has good performance. In addition, the feasibility of wearable motion sensors in business English teaching is verified by the establishment of an experimental classes, which can promote students' English learning better.

Key words

Wearable motion sensor, Business English, Business English Teaching

Digital Object Identifier (DOI)

Publication information

Volume 19, Issue 3 (September 2022)
Year of Publication: 2022
ISSN: 2406-1018 (Online)
Publisher: ComSIS Consortium

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How to cite

Lu, D., Guo, F.: Application of Wearable Motion Sensor in Business English Teaching. Computer Science and Information Systems, Vol. 19, No. 3, 1481-1498. (2022),